Introduction to Hadoop
Introduction to Hadoop Course Online by Checkmate IT Tech will be a transformative journey, elevating your expertise and mastering essential skills. Position yourself for success in the dynamic field of Big Data by enrolling today. Unlock new career opportunities!
- 10+ Courses
- 30+ Projects
- 400 Hours
Introduction to Hadoop Training is suitable for the following target audiences:
Data Analysts and Scientists: Scientists and data analysts are professionals that want to improve their abilities to handle and analyze large amounts of data.
Software developers: Developers who want to use Hadoop’s distributed computing capabilities to create data-intensive applications.
System Administrators: System administrators are IT professionals in charge of large-scale systems for processing and storing data.
Professionals in business intelligence: Those making the switch to big data technologies for more sophisticated analytics.
Students and Novices: Individuals who are unfamiliar with big data and are looking to launch their careers by gaining a basic understanding of Hadoop.
Big Data Engineer: Using Hadoop to design and oversee massive data processing systems.
Hadoop Developer: Using the tools in the Hadoop ecosystem to create apps and workflows.
Data Scientist: Preparing and analyzing big datasets with Hadoop to get useful information.
Data Engineer: Building and refining data structures and pipelines for big data solutions is the responsibility of data engineers.
System Administrator (Hadoop): Managing Hadoop clusters, maintaining performance, and managing configurations are the responsibilities of a system administrator.
Professionals with Hadoop training are in high demand in the US and Canada, with industries including banking, healthcare, retail, technology, and telecommunications providing competitive pay and chances for advancement in the big data field.
- What is Big Data? Key characteristics (5 Vs)
- Challenges of traditional data systems
- Introduction to Hadoop and its purpose
- Overview of Hadoop Ecosystem
- Use cases and real-world applications
- Hands On : Install Hadoop (local/pseudo-distributed mode)
- Hadoop Core: HDFS and MapReduce
- HDFS deep dive: Blocks, replication, NameNode, DataNode
- MapReduce overview
- Intro to Hadoop 2.x & YARN (Yet Another Resource Negotiator)
- Hands On: Explore HDFS commands (put, get, ls, cat)
- HDFS data flow: Read & Write operations
- File system hierarchy
- File permissions and access control
- Fault tolerance and high availability
- Hands On: HDFS CLI exercises and basic shell scripting
- Anatomy of a MapReduce job (Mapper, Reducer, Driver)
- InputFormat & OutputFormat
- Combiner and Partitioner
- Use case: Word count example
- Hands On: Write and run a simple MapReduce job
- YARN architecture: ResourceManager, NodeManager, ApplicationMaster
- Job scheduling and execution
- Monitoring jobs and logs
- Hands On: Submit jobs and track them on ResourceManager UI
- Introduction to Hive: Hive vs. RDBMS and Hive architecture (Metastore, Driver, Compiler)
- HiveQL basics: Create tables, load data, run queries
- Hands On : Create a Hive table and perform basic queries
- Partitioning and bucketing in Hive
- Data types and file formats (Text, ORC, Parquet)
- External vs. managed tables
- Join operations and aggregations
- Hands On: Load large datasets and analyze using Hive
- Final-project and review of key concepts and hands-on tasks
- Career tips and Hadoop certification overview
Note: Curriculum will be modified as per latest industry standards.
This course is ideal for beginners—students, IT professionals, or career changers—interested in learning the basics of Hadoop and Big Data technologies.
No prior programming experience is required. Basic knowledge of computers and command-line usage is helpful but not mandatory.
The course covers Hadoop fundamentals including HDFS, MapReduce, YARN, and introductory Hive usage. You’ll also work on hands-on labs and a final -pro
You’ll get an overview of the ecosystem, but the course mainly focuses on Hadoop core components like HDFS, MapReduce, YARN, and Hive.
Yes! Each week includes hands -on exercises where you’ll use real Hadoop tools and run basic commands and queries.
Students Will need a computer with internet access. Installation guides are provided for setting up Hadoop in pseudo-distributed mode or using a virtual machine.
The course runs for 8 weeks, with one topic per week. Each week includes lectures, readings, labs, and optional quizzes.
You can enroll via our website or contact our support team directly via email or phone. We’ll guide you through the quick and easy registration process.
https://checkmateittech.com/
Email info@checkmateittech.com OR Call Us +1-347-4082054
Yes, students who complete the course content and final project will receive a certificate of completion.
You can pursue more advanced training in tools like Apache Spark, HBase, or cloud-based data engineering. This course also prepares you for entry-level roles in Big Data.
This course is designed specifically for beginners, with a strong focus on clarity, practical application, and building foundational confidence in Hadoop technologies.
We currently offer online sessions with flexible weekday/weekend batches. All sessions are recorded. You’ll have access to the recordings, along with support from instructors and peers in our learning portal.
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Job opportunities in USA and Canada
Big Data Engineer: Using Hadoop to design and oversee massive data processing systems.
Hadoop Developer: Using the tools in the Hadoop ecosystem to create apps and workflows.
Data Scientist: Preparing and analyzing big datasets with Hadoop to get useful information.
Data Engineer: Building and refining data structures and pipelines for big data solutions is the responsibility of data engineers.
System Administrator (Hadoop): Managing Hadoop clusters, maintaining performance, and managing configurations are the responsibilities of a system administrator.
Professionals with Hadoop training are in high demand in the US and Canada, with industries including banking, healthcare, retail, technology, and telecommunications providing competitive pay and chances for advancement in the big data field.
